P09 Validation of a novel biomarker model for the prediction of non-alcoholic steatohepatitis in patients with non-alcoholic fatty liver disease. (6th September 2011) - Tanwar, S; Trembling, P; Guha, I N; Parkes, J; Kaye, P; Burt, A D; Ryder, S D; Aithal, G P; Day, C P; Rosenberg, W M
Abstract : Introduction: The detection of non-alcoholic steatohepatitis (NASH) within non-alcoholic fatty liver disease (NAFLD) is important both for ascertaining prognosis and the stratification of patients for existing interventions and emerging therapies. Liver biopsy is considered the reference standard for assessing NASH. The aim of this study was to develop a biomarker of NASH which would be able to detect NASH prior to the development of significant hepatic fibrosis. Candidate biomarkers of hepatic inflammation, apoptosis and liver fibrosis were selected on the basis of biological plausibility and previous association with NAFLD. Method: 172 patients with NAFLD and no evidence of other liver disease were consecutively recruited from two centres. 84 patients from the first centre were included as a training cohort and 88 patients from the second centre as a validation cohort. Liver biopsies were performed on all patients and scored using the NAFLD activity score (NAS). 36 patients with advanced fibrosis were excluded from the analysis. Serum samples were taken on all patients and tested for five matrix proteins (HA, P3NP, TIMP-1, Procollagen 4 and YKL-40) and 19 haematological and biochemical parameters including HOMA-IR. Stepwise multiple linear regression was used to determine the relationship of the multiple variables to the NAS score. Results: A model combining terminal peptide of pro-collagen III (P3NP) and tissue inhibitor of matrix metalloproteinase 1 (TIMP-1) was found to significantly correlate with the NAS score in the training cohort (R=0.643, R2=0.413, p<0.0000001). The regression model was then validated in the second patient cohort. AUROC were calculated for the ability of the model to discriminate between differing degrees of NAS. Conclusion: This model appears to have good diagnostic performance for the detection of NASH in both the training and validation cohorts. Our results appear promising and if confirmed in further studies this model will be of clinical utility in detecting the minority of patients with NAFLD who have NASH and are at risk of developing progressive liver disease.